Project description:We aimed to identify urinary exosomal ncRNAs as novel biomarkers for diagnosis of Chronic Kidney Disease (CKD) for this, we examined 15 exosomal ncRNA profiles in urine samples from CKD patients from four different stages (I, II, III and IV) and compared them to 10 healthy controls. We identified a significant number of novel, differentially expressed ncRNAs in CKD patients compared to healthy, which might be employed as early diagnostic markers in CKD in the future.
Project description:BackgroundAlzheimer's disease (AD) is a complex and heterogeneous disease, which requires reliable biomarkers for diagnosis and monitoring disease activity. Preanalytical protocol and technical variability associated with biomarker immunoassays makes comparability of biomarker data across multiple cohorts difficult. This study aimed to compare cerebrospinal fluid (CSF) biomarker results across independent cohorts, including participants spanning the AD continuum.MethodsMeasured on the NeuroToolKit (NTK) prototype panel of immunoassays, 12 CSF biomarkers were evaluated from three cohorts (ALFA+, Wisconsin, and Abby/Blaze). A correction factor was applied to biomarkers found to be affected by preanalytical procedures (amyloid-β1-42, amyloid-β1-40, and alpha-synuclein), and results between cohorts for each disease stage were compared. The relationship between CSF biomarker concentration and cognitive scores was evaluated.ResultsBiomarker distributions were comparable across cohorts following correction. Correlations of biomarker values were consistent across cohorts, regardless of disease stage. Disease stage differentiation was highest for neurofilament light (NfL), phosphorylated tau, and total tau, regardless of the cohort. Correlation between biomarker concentration and cognitive scores was comparable across cohorts, and strongest for NfL, chitinase-3-like protein-1 (YKL40), and glial fibrillary acidic protein.DiscussionThe precision of the NTK enables merging of biomarker datasets, after correction for preanalytical confounders. Assessment of multiple cohorts is crucial to increase power in future studies into AD pathogenesis.
Project description:Recent GWAS studies have made extensive use of large eQTL data sets to functionally
annotate index SNPs. With a large number of association signals located outside coding
regions there has been an intense search among sequence variants affecting gene
expression at the transcriptional level. However, little progress has been made in mapping
regulatory variants that affect protein levels at the translational or post-translational level. It is
now possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins by
mass spectrometry. We have established a collaboration with a longitudinal, family-based
study in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295
individuals) and has follow up data for 10 years (three visits). We have undertaken a pilot
study in a focus set of 257 subjects from 79 families with the aim to integrate GWAS,
transcriptomic and DNA methylation data with proteomic data on a set of 100 proteins
measured in PBMCs. We have already generated GWAS data using Illumina's core-exome
chip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq to
generate transcriptomic data of the corresponding PBMCs.
This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
Project description:The lack of knowledge about the onset and progression of Parkinson's disease (PD) hampers its early diagnosis and treatment. Metabolomics might shed light on the PD imprint seeking a broader view of the biochemical remodeling induced by this disease in an early and pre-symptomatic stage and unveiling potential biomarkers. To achieve this goal, we took advantage of the great potential of the European Prospective Study on Nutrition and Cancer (EPIC) cohort to apply metabolomics searching for early diagnostic PD markers. This cohort consisted of healthy volunteers that were followed for around 15 years until June 2011 to ascertain incident PD. For this untargeted metabolomics-based study, baseline preclinical plasma samples of 39 randomly selected individuals that developed PD (Pre-PD group) and the corresponding control group were analyzed using a multiplatform approach. Data were statistically analyzed and exposed alterations in 33 metabolites levels, including significantly lower levels of free fatty acids (FFAs) in the preclinical samples from PD subjects. These results were then validated by adopting a targeted HPLC-QqQ-MS approach. After integrating all the metabolites affected, our finding revealed alterations in FFAs metabolism, mitochondrial dysfunction, oxidative stress, and gut-brain axis dysregulation long before the development of PD hallmarks. Although the biological purpose of these events is still unknown, the remodeled metabolic pathways highlighted in this work might be considered worthy prognostic biomarkers of early prodromal PD. The findings revealed by this work are of inestimable value since this is the first study conducted with samples collected many years before the disease development.
Project description:Introduction: MicroRNAs (miRNAs) are small, non-coding RNA molecules involved in post-transcriptional gene regulation and have recently been shown to play a role in cancer metastasis. In solid tumors, especially breast cancer, alterations in miRNA expression contribute to cancer pathogenesis, including metastasis. Considering the emerging role of miRNAs in metastasis, the identification of predictive markers is necessary to further understanding of stage-specific breast cancer development. This is a retrospective analysis that aimed to identify molecular biomarkers related to distant breast cancer metastasis development.<br><br>Methods: A retrospective case cohort study was performed in 64 breast cancer patients treated during the period from 1998-2001. The case group (n=29) consisted of patients with a poor prognosis who presented with breast cancer recurrence or metastasis during follow up. The control group (n=35) consisted of a random sample of patients with a good prognosis who did not develop breast cancer recurrence or metastasis. These patient groups were stratified according to TNM clinical stage (CS) I, II and III, and the main clinical features of the patients were homogeneous. miRNA profiling was performed using formalin-fixed, paraffin-embedded tumors. Biomarkers related to metastatic potential were identified independent of clinical stage, and a cutoff point was selected based on the optimal sensitivity and specificity (ROC curve). Finally, a hazard risk analysis of these biomarkers was performed to evaluate their relation to metastatic potential. <br><br>Results: miRNA expression profiling identified several miRNAs that were either specific and shared across all clinical stages (p?0.05). Among these, we identified miRNAs previously associated with cell motility (let-7 family), cell proliferation and invasion (hsa-miR-16 and has-miR-205) and distant metastasis (hsa-miR-21). In addition, hsa-miR-494 and hsa-miR-21 were up-regulated in metastatic cases of CSI and II. Furthermore, the combination of the 3 miRNAs identified for CSII (hsa-miR-494, hsa-miR-183 and hsa-miR-21) was significant and were a more effective risk marker compared to the single miRNAs. <br><br>Conclusions: Women with metastatic breast cancer, especially CSII, presented up-regulated levels of miR-183, miR-494 and miR-21, which were associated with a poor prognosis. These miRNAs therefore represent new risk biomarkers of breast cancer metastasis and may be useful for future targeted therapies.
Project description:The IBD-Character cohort (Edinburgh, Oslo, Örebro, Linköping, Zaragoza, Maastricht) included patients with inflammatory bowel diseases (IBD: Crohn's disease, ulcerative colitis) recruited at diagnosis and non-IBD controls. Paired-end RNA sequencing was used for whole blood expression profiling. Raw and normalized counts tables are provided.
Project description:The pathogen and host factors that contribute to the establishment of foot-and-mouth disease virus (FMDV) persistence are currently not understood. Using primary bovine soft palate multilayers in combination with RNA sequencing, we analyzed the transcriptional responses during acute and persistent FMDV infection.
Project description:Polycystic Kidney Disease (PKD) is a genetic disease of the kidney characterized by the gradual replacement of normal kidney parenchyma by fluid-filled cysts and fibrotic tissue. Autosomal Dominant Polycystic Kidney Disease (ADPKD) is caused by mutations in the PKD1 or PKD2 gene. Here we present an RNASeq experiment designed to investigate the effect of a kidney specific and Tamoxifen inducible knockout of the Pkd1 gene in mice. 7 mice were grouped into two groups, 4 Tamoxifen treated mice which develop an adult onset Polycystic Kidney Disease phenotype and 3 untreated mice which have WT phenotype.
Project description:It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein-protein or gene-gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed.
Project description:Subtypes of innate lymphoid cells (ILC), defined by effector function and transcription factor expression, have recently been identified. In the adult, ILC derive from common lymphoid progenitors in bone marrow, although transcriptional regulation of the developmental pathways involved remains poorly defined. TOX is required for development of lymphoid tissue inducer cells, a type of ILC3 required for lymph node organogenesis, and NK cells, a type of ILC1. We show here that production of multiple ILC lineages requires TOX, as a result of TOX-dependent development of common ILC progenitors. Comparative transcriptome analysis demonstrated failure to induce various aspects of the ILC gene program in the absence of TOX, implicating this nuclear factor as a key early determinant of ILC lineage specification. TOX KO vs. wild tyype